Chapter 3: Representing Knowledge in Computer Introduction (Representing knowledge, Metrics for assessing knowledge representation schemes), Logic representation, Inference rules, Semantics networks, Frames and Scripts, Decision trees. | Chapter 3 Representing Knowledge in Computer K216 C: Studies on Intelligence School of Knowledge Science JAIST TuBao Ho 1 Outline of chapter 3 1. Introduction 2. 3. 4. 5. 6. Representing knowledge Metrics for assessing knowledge representation schemes Logic representation Inference rules Semantics networks Frames and Scripts Decision trees 2 Introduction declarative knowledge is knowledge about things location of JAIST, its transport links “JAIST is in Tatsunokuchi”, “Hokuriku Railroad Ishikawa line goes from Nomachi to Tsurugi” procedural knowledge is knowledge about how to do things how to get to JAIST “Take the Hokuriku Railroad, Ishikawa line to go to Tsurugi”, “Get on the JAIST shuttle” 3 Introduction domain-specific knowledge: specific knowledge on a particular subject Example: “JAIST shuttle goes from Tsurugi to JAIST” domain-independent knowledge: general knowledge that applies throughout our experience Example: “shuttle bus is a means of transport” Common sense: common knowledge about the world that is possessed by every schoolchild. It is evident for human but not for machine Example: “Bird can fly” 4 Introduction In order to make use of knowledge in AI and intelligent systems we need to get it from the source (knowledge acquisition) and represent it in a form usable by the machine Human knowledge is usually expressed through language, which cannot be accurately understood by machine The representation of knowledge in computer must therefore be both appropriate for the computer to use and allow easy and accurate encoding from the .
